It is widely believed that the emergence of ubiquitous computing and sensor networks, will effectuate a gradual elimination of personal computing. This will have profound impacts on how networked and connected systems work today. Particularly, smart environment architecture and components level interoperation in such environment may alter.
In the smart environment architecture, as is known a Pervasive awareness systems (PASs) collect awareness information from sensors and devices and present it to remote users by using awareness objects such as ambient displays, lamps and picture frames. Such systems typically modeled with a pervasive awareness management framework for supporting the conception, design and realization of applications that foster discovery, connectedness between user and devices.
In such smart environment architecture, device discovery enables extraction of information from the devices according to their characteristics. Hitherto, various systems and methods are provided for performing a device discovery and predominantly for addressing problems associated with an efficient device discovery. However, following the discovery, an ability of a smart system for prioritization and interoperations there between the devices is not disclosed in the art. An effective prioritization results in an optimized interoperation between devices, which collectively enhances the quality of user experience related with the devices. In turn, user friendly PASs allow users as well as applications to discover and interact with the most appropriate and relevant services provided by many devices/sensors in the environment.
In a smart environment the devices are configured to function according to the attributes of the devices, as services in any smart space are registered and looked up by their attributes.
A challenge is also faced in effective device prioritization and optimization of device interoperation while performing device capability negotiation during device discovery. Various discovery mechanisms have been proposed, designed, and implemented. While they share the main goal of providing a mechanism for service association and discovery of the devices, they vary significantly in aspects like the architectural design and working environment (i.e., LANs, mobile ad hoc, Internet). Current discovery protocols, such as Jini, UPnP, Salutation, SLP, Ninja/SDS, INS/Twine, and UDDI, are not suitable for pervasive computing environments.
The situation based applications known in the art are modeled with a predefined set of contexts, and hence are not dynamic. Accordingly, these applications do not consider contextual information in a flexible manner while discovering services, and as a result, they fail to provide the most relevant and appropriate services for users, hampering user experience.
To achieve more flexible situation awareness, the applications should have the ability to discover smart sensing devices with a complete understanding of their attributes and collect sensing data in a timely and organized fashion.
In addition to sensing physical surroundings in the context-aware systems, an efficient processing of data collected from sensors is still a challenge. As while data processing, complexities arise for resolution of attributes such as location, identity, timestamp, etc. and even more for representation of these resolved attributes during actual communication with the sensor.
There are conventional systems that exist to associate device descriptors with the discovered devices using different discovery protocol. The conventional systems teaches about a method for target discovery in an iSCSI storage area network in which the host initiator uses a target discovery manager which communicates with the target devices through a network. This system may provide a clear way to map host side enumerations of target devices to different iSCSI discovery protocols. However, this system takes into account the discovery protocol and its prioritization only for later device interaction. It does not facilitate choosing the right sort of devices for a given type of exchange for later interaction.
Another conventional system may associate unified device descriptors (UDD) by analyzing and discovering electronic documents in an intranet using semantic analysis. Intranet includes multiple web sites. This system emphasizes on the electronic files in the intranet, it deals with the data content of the files, the type of files can be html or non-html based thus the system does not state about smart devices, here the electronic files are considered as devices and also does have to address much of heterogeneity.
Another conventional system may provide a method and system for customized data delivery and network configuration by performing the aggregation of device attributes using a specific network architecture having multiple access gateways. However it does not propose any method, system and devices for achieving faster interoperation between the devices.
Some of the prior art as discussed above teaches device discovery, device attributes, semantic analysis, device interoperation, and associating uniform device descriptor file with digital device of the set of digital devices operating in a networked environment. The systems in the state of the art are not precisely aware of any mechanism of generating generic device attributes of devices in a smart environment during the device discovery process to help to reduce the time and complexity in device prioritization and device interoperation for a required type of interaction.
Thus, a heretofore unaddressed need exists in the industry to address the aforementioned deficiencies and inadequacies.